The Gait Identification Challenge Problem: Data Sets and Baseline Algorithm
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
A New Attempt to Gait-based Human Identification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Individual Recognition by Kinematic-Based Gait Analysis
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Silhouette-Based Human Identification from Body Shape and Gait
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Gait shape estimation for identification
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Statistical feature fusion for gait-based human recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Hi-index | 0.00 |
Human gait properties can be affected by various environmental contexts such as walking surface and carrying objects. In this paper, we propose a novel approach for individual recognition by combining different gait classifiers with the knowledge of environmental contexts to improve the recognition performance. Different classifiers are designed to handle different environmental contexts, and context specific features are explored for context characterization. In the recognition procedure, we can determine the probability of environmental contexts in any probe sequence according to its context features, and apply the probabilistic classifier combination strategies for the recognition. Experimental results demonstrate the effectiveness of the proposed approach.